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I fine-tuned tsn using my own dataset during experiments. The results I got are working fine in webcam_demo. But I wanted to be able to identify each picture of the video, so I tried long_video_demo.py, but I found that the same video was shot on the screen through the webcam and the video was directly identified, the results were very different. , but the results of Webcam are closer to correct, while long_video_demo cannot get good results, and even recognizes errors. My config and label_map both use the same one. Does anyone know what could cause this to happen?
Reproduces the problem - code sample
No response
Reproduces the problem - command or script
No response
Reproduces the problem - error message
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Additional information
No response
The text was updated successfully, but these errors were encountered:
Branch
main branch (1.x version, such as
v1.0.0
, ordev-1.x
branch)Prerequisite
Environment
sys.platform: win32
Python: 3.8.19 (default, Mar 20 2024, 19:55:45) [MSC v.1916 64 bit (AMD64)]
CUDA available: True
MUSA available: False
numpy_random_seed: 2147483648
GPU 0: NVIDIA GeForce RTX 4080
CUDA_HOME: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v11.2
NVCC: Cuda compilation tools, release 11.2, V11.2.67
GCC: n/a
PyTorch: 1.13.1
PyTorch compiling details: PyTorch built with:
-openmp:experimental -IC:/cb/pytorch_1000000000000/work/mkl/include -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOCUPTI -DUSE_FBGEMM -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO, LAPACK_INFO=mkl, PERF_WITH_AVX=1
, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.13.1, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=OFF, USE_NNPACK=OFF, USE_OPENMP=ON, USE_ROCM=OFF,
TorchVision: 0.14.1
OpenCV: 4.10.0
MMEngine: 0.10.4
MMAction2: 1.2.0+4d6c934
MMCV: 2.1.0
MMDetection: 3.2.0
MMPose: 1.3.2
Describe the bug
I fine-tuned tsn using my own dataset during experiments. The results I got are working fine in webcam_demo. But I wanted to be able to identify each picture of the video, so I tried long_video_demo.py, but I found that the same video was shot on the screen through the webcam and the video was directly identified, the results were very different. , but the results of Webcam are closer to correct, while long_video_demo cannot get good results, and even recognizes errors. My config and label_map both use the same one. Does anyone know what could cause this to happen?
Reproduces the problem - code sample
No response
Reproduces the problem - command or script
No response
Reproduces the problem - error message
No response
Additional information
No response
The text was updated successfully, but these errors were encountered: